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Semantic Web for the Working Ontologist - Effective Modeling in RDFS and OWL

Semantic Web for the Working Ontologist - Effective Modeling in RDFS and OWL

of: Dean Allemang, James Hendler

Elsevier Trade Monographs, 2008

ISBN: 9780080558387 , 352 Pages

Format: PDF, ePUB, Read online

Copy protection: DRM

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Price: 51,11 EUR



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Semantic Web for the Working Ontologist - Effective Modeling in RDFS and OWL


 

Front Cover

1

Semantic Web for the Working Ontologist Modeling in RDF, RDFS and OWL

4

Copyright Page

5

Contents

8

Preface

14

About the Authors

18

Chapter 1: What Is the Semantic Web?

20

What Is a Web?

20

Smart Web, Dumb Web

21

Smart Web Applications

22

A Connected Web Is a Smarter Web

23

Semantic Data

24

A Distributed Web of Data

25

Features of a Semantic Web

26

What about the Round-Worlders?

28

To Each Their Own

29

There's Always One More

30

Summary

31

Fundamental Concepts

32

Chapter 2: Semantic Modeling

34

Modeling for Human Communication

36

Explanation and Prediction

38

Mediating Variability

40

Variation and Classes

41

Variation and Layers

42

Expressivity in Modeling

45

Summary

47

Fundamental Concepts

48

Chapter 3: RDF-The Basis of the Semantic Web

50

Distributing Data Across the Web

51

Merging Data from Multiple Sources

55

Namespaces, URIs, and Identity

56

Expressing URIs in Print

59

Standard Namespaces

62

Identifiers in the RDF Namespace

63

Challenge: RDF and Tabular Data

64

Higher-Order Relationships

68

Alternatives for Serialization

70

N-Triples

70

Notation 3 RDF (N3)

71

RDF/XML

72

Blank Nodes

73

Ordered Information in RDF

75

Summary

75

Fundamental Concepts

76

Chapter 4: Semantic Web Application Architecture

78

RDF Parser/Serializer

79

Other Data Sources-Converters and Scrapers

80

RDF Store

83

RDF Data Standards and Interoperability of RDF Stores

85

RDF Query Engines and SPARQL

85

Comparison to Relational Queries

91

Application Code

92

RDF-Backed Web Portals

94

Data Federation

94

Summary

95

Fundamental Concepts

96

Chapter 5: RDF and Inferencing

98

Inference in the Semantic Web

99

Virtues of Inference-Based Semantics

101

Where Are the Smarts?

102

Asserted Triples versus Inferred Triples

104

When Does Inferencing Happen?

106

Inferencing as Glue

107

Summary

108

Fundamental Concepts

109

Chapter 6: RDF Schema

110

Schema Languages and their Functions

110

What Does it Mean? Semantics as Inference

112

The RDF Schema Language

114

Relationship Propagation through rdfs:subPropertyOf

114

Typing Data by Usage-rdfs:domain and rdfs:range

117

Combination of Domain and Range with rdfs:subClassOf

118

RDFS Modeling Combinations and Patterns

121

Set Intersection

121

Property Intersection

123

Set Union

124

Property Union

125

Property Transfer

125

Challenges

127

Term Reconciliation

127

Instance-Level Data Integration

129

Readable Labels with rdfs:label

129

Data Typing Based on Use

130

Filtering Undefined Data

134

RDFS and Knowledge Discovery

134

Modeling with Domains and Ranges

135

Multiple Domains/Ranges

135

Nonmodeling Properties in RDFS

139

Cross-Referencing Files: rdfs:seeAlso

139

Organizing Vocabularies: rdfs:isDefinedBy

140

Model Documentation: rdfs:comment

140

Summary

140

Fundamental Concepts

141

Chapter 7: RDFS-Plus

142

Inverse

143

Challenge: Integrating Data that Do Not Want to Be Integrated

144

Challenge: Using the Modeling Language to Extend the Modeling Language

146

Challenge: The Marriage of Shakespeare

148

Symmetric Properties

148

Using OWL to Extend OWL

149

Transitivity

150

Challenge: Relating Parents to Ancestors

151

Challenge: Layers of Relationships

152

Managing Networks of Dependencies

153

Equivalence

158

Equivalent Classes

160

Equivalent Properties

161

Same Individuals

162

Challenge: Merging Data from Different Databases

165

Computing Sameness-Functional Properties

168

Functional Properties

169

Inverse Functional Properties

170

Combining Functional and Inverse Functional Properties

173

A Few More Constructs

174

Summary

175

Fundamental Concepts

176

Chapter 8: Using RDFS-Plus in the Wild

178

SKOS

178

Semantic Relations in SKOS

182

Meaning of Semantic Relations

184

Special Purpose Inference

185

Published Subject Indicators

187

SKOS in Action

187

FOAF

188

People and Agents

189

Names in FOAF

190

Nicknames and Online Names

190

Online Persona

191

Groups of People

192

Things People Make and Do

193

Identity in FOAF

194

It's Not What You Know, It's Who You Know

195

Summary

196

Fundamental Concepts

197

Chapter 9: Basic OWL

198

Restrictions

198

Example: Questions and Answers

199

Adding "Restrictions"

202

Kinds of Restrictions

203

Challenge Problems

215

Challenge: Local Restriction of Ranges

215

Challenge: Filtering Data Based on Explicit Type

217

Challenge: Relationship Transfer in SKOS

221

Relationship Transfer in FOAF

223

Alternative Descriptions of Restrictions

228

Summary

229

Fundamental Concepts

230

Chapter 10: Counting and Sets in OWL

232

Unions and Intersections

233

Closing the World

235

Enumerating Sets with owl:oneOf

235

Differentiating Individuals with owl:differentFrom

237

Differentiating Multiple Individuals

238

Cardinality

241

Small Cardinality Limits

244

Set Complement

245

Disjoint Sets

247

Prerequisites Revisited

250

No Prerequisites

251

Counting Prerequisites

252

Guarantees of Existence

253

Contradictions

254

Unsatisfiable Classes

256

Propagation of Unsatisfiable Classes

256

Inferring Class Relationships

257

Reasoning with Individuals and with Classes

262

Summary

263

Fundamental Concepts

264

Chapter 11: Using OWL in the Wild

266

The Federal Enterprise Architecture Reference Model Ontology

267

Reference Models and Composability

268

Resolving Ambiguity in the Model: Sets Versus Individuals

270

Constraints Between Models

272

OWL and Composition

274

owl:Ontology

274

owl:imports

275

Advantages of the Modeling Approach

276

The National Cancer Institute Ontology

277

Requirements of the NCI Ontology

278

Upper-Level Classes

280

Describing Classes in the NCI Ontology

285

Instance-Level Inferencing in the NCI Ontology

286

Summary

288

Fundamental Concepts

289

Chapter 12: Good and Bad Modeling Practices

290

Getting Started

290

Know What You Want

291

Inference Is Key

292

Modeling for Reuse

293

Insightful Names Versus Wishful Names

293

Keeping Track of Classes and Individuals

294

Model Testing

296

Common Modeling Errors

296

Rampant Classism (Antipattern)

296

Exclusivity (Antipattern)

301

Objectification (Antipattern)

304

Managing Identifiers for Classes (Antipattern)

307

Creeping Conceptualization (Antipattern)

308

Summary

309

Fundamental Concepts

310

Chapter 13: OWL Levels and Logic

312

OWL Full versus OWL DL

313

Provable Models

Provable Models

Class/Individual Separation

317

InverseFunctional Datatypes

317

OWL Lite

318

Other Subsets of OWL

318

Beyond OWL 1.0

319

Metamodeling

319

Multipart Properties

320

Qualified Cardinality

321

Multiple Inverse Functional Properties

321

Rules

322

Summary

323

Fundamental Concepts

323

Chapter 14: Conclusions

326

Appendix: Frequently Asked Questions

332

Further Reading

336

Index

340